MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible

Marcely Zanon Boito; William Havard; Mahault Garnerin; Eric Le Ferrand; Besacier Laurent

MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible

Marcely Zanon Boito, William Havard, Mahault Garnerin, Eric Le Ferrand, Besacier Laurent

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review

Abstract

The CMU Wilderness Multilingual Speech Dataset (Black, 2019) is a newly published multilingual speech dataset based on recorded readings of the New Testament. It provides data to build Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) models for potentially 700 languages. However, the fact that the source content (the Bible) is the same for all the languages is not exploited to date.Therefore, this article proposes to add multilingual links between speech segments in different languages, and shares a large and clean dataset of 8,130 parallel spoken utterances across 8 languages (56 language pairs). We name this corpus MaSS (Multilingual corpus of Sentence-aligned Spoken utterances). The covered languages (Basque, English, Finnish, French, Hungarian, Romanian, Russian and Spanish) allow researches on speech-to-speech alignment as well as on translation for typologically different language pairs. The quality of the final corpus is attested by human evaluation performed on a corpus subset (100 utterances, 8 language pairs). Lastly, we showcase the usefulness of the final product on a bilingual speech retrieval task.

Original language	English
Title of host publication	Proceedings of The 12th Language Resources and Evaluation Conference
Editors	Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Publisher	European Language Resources Association (ELRA)
Pages	6486-6493
Number of pages	8
Publication status	Published - 2020
Externally published	Yes
Event	12th Language Resources and Evaluation Conference: LREC - Marseille, France Duration: 11 May 2020 → 16 May 2020 Conference number: 12th https://lrec2020.lrec-conf.org/en/

Conference

Conference	12th Language Resources and Evaluation Conference
Country	France
City	Marseille
Period	11/05/20 → 16/05/20
Internet address	https://lrec2020.lrec-conf.org/en/

Access to Document

https://www.aclweb.org/anthology/2020.lrec-1.799Licence: CC BY

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Boito, M. Z., Havard, W., Garnerin, M., Le Ferrand, E., & Laurent, B. (2020). MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible. In N. Calzolari, F. Béchet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, & S. Piperidis (Eds.), Proceedings of The 12th Language Resources and Evaluation Conference (pp. 6486-6493). European Language Resources Association (ELRA). https://www.aclweb.org/anthology/2020.lrec-1.799

Boito, Marcely Zanon ; Havard, William ; Garnerin, Mahault ; Le Ferrand, Eric ; Laurent, Besacier. / MaSS : A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible. Proceedings of The 12th Language Resources and Evaluation Conference. editor / Nicoletta Calzolari ; Frédéric Béchet ; Philippe Blache ; Khalid Choukri ; Christopher Cieri ; Thierry Declerck ; Sara Goggi ; Hitoshi Isahara ; Bente Maegaard ; Joseph Mariani ; Hélène Mazo ; Asuncion Moreno ; Jan Odijk ; Stelios Piperidis. European Language Resources Association (ELRA), 2020. pp. 6486-6493

@inproceedings{97f9755f01e145fd9538fefa3ddd2ce9,

title = "MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible",

abstract = "The CMU Wilderness Multilingual Speech Dataset (Black, 2019) is a newly published multilingual speech dataset based on recorded readings of the New Testament. It provides data to build Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) models for potentially 700 languages. However, the fact that the source content (the Bible) is the same for all the languages is not exploited to date.Therefore, this article proposes to add multilingual links between speech segments in different languages, and shares a large and clean dataset of 8,130 parallel spoken utterances across 8 languages (56 language pairs). We name this corpus MaSS (Multilingual corpus of Sentence-aligned Spoken utterances). The covered languages (Basque, English, Finnish, French, Hungarian, Romanian, Russian and Spanish) allow researches on speech-to-speech alignment as well as on translation for typologically different language pairs. The quality of the final corpus is attested by human evaluation performed on a corpus subset (100 utterances, 8 language pairs). Lastly, we showcase the usefulness of the final product on a bilingual speech retrieval task.",

author = "Boito, {Marcely Zanon} and William Havard and Mahault Garnerin and {Le Ferrand}, Eric and Besacier Laurent",

year = "2020",

language = "English",

pages = "6486--6493",

editor = "Nicoletta Calzolari and Fr{\'e}d{\'e}ric B{\'e}chet and Philippe Blache and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and H{\'e}l{\`e}ne Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis",

booktitle = "Proceedings of The 12th Language Resources and Evaluation Conference",

publisher = "European Language Resources Association (ELRA)",

note = "12th Language Resources and Evaluation Conference : LREC ; Conference date: 11-05-2020 Through 16-05-2020",

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Boito, MZ, Havard, W, Garnerin, M, Le Ferrand, E & Laurent, B 2020, MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible. in N Calzolari, F Béchet, P Blache, K Choukri, C Cieri, T Declerck, S Goggi, H Isahara, B Maegaard, J Mariani, H Mazo, A Moreno, J Odijk & S Piperidis (eds), Proceedings of The 12th Language Resources and Evaluation Conference. European Language Resources Association (ELRA), pp. 6486-6493, 12th Language Resources and Evaluation Conference, Marseille, France, 11/05/20. <https://www.aclweb.org/anthology/2020.lrec-1.799>

MaSS : A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible. / Boito, Marcely Zanon; Havard, William; Garnerin, Mahault; Le Ferrand, Eric; Laurent, Besacier.

Proceedings of The 12th Language Resources and Evaluation Conference. ed. / Nicoletta Calzolari; Frédéric Béchet; Philippe Blache; Khalid Choukri; Christopher Cieri; Thierry Declerck; Sara Goggi; Hitoshi Isahara; Bente Maegaard; Joseph Mariani; Hélène Mazo; Asuncion Moreno; Jan Odijk; Stelios Piperidis. European Language Resources Association (ELRA), 2020. p. 6486-6493.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review

TY - GEN

T1 - MaSS

T2 - 12th Language Resources and Evaluation Conference

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AU - Havard, William

AU - Garnerin, Mahault

AU - Le Ferrand, Eric

AU - Laurent, Besacier

N1 - Conference code: 12th

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N2 - The CMU Wilderness Multilingual Speech Dataset (Black, 2019) is a newly published multilingual speech dataset based on recorded readings of the New Testament. It provides data to build Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) models for potentially 700 languages. However, the fact that the source content (the Bible) is the same for all the languages is not exploited to date.Therefore, this article proposes to add multilingual links between speech segments in different languages, and shares a large and clean dataset of 8,130 parallel spoken utterances across 8 languages (56 language pairs). We name this corpus MaSS (Multilingual corpus of Sentence-aligned Spoken utterances). The covered languages (Basque, English, Finnish, French, Hungarian, Romanian, Russian and Spanish) allow researches on speech-to-speech alignment as well as on translation for typologically different language pairs. The quality of the final corpus is attested by human evaluation performed on a corpus subset (100 utterances, 8 language pairs). Lastly, we showcase the usefulness of the final product on a bilingual speech retrieval task.

AB - The CMU Wilderness Multilingual Speech Dataset (Black, 2019) is a newly published multilingual speech dataset based on recorded readings of the New Testament. It provides data to build Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) models for potentially 700 languages. However, the fact that the source content (the Bible) is the same for all the languages is not exploited to date.Therefore, this article proposes to add multilingual links between speech segments in different languages, and shares a large and clean dataset of 8,130 parallel spoken utterances across 8 languages (56 language pairs). We name this corpus MaSS (Multilingual corpus of Sentence-aligned Spoken utterances). The covered languages (Basque, English, Finnish, French, Hungarian, Romanian, Russian and Spanish) allow researches on speech-to-speech alignment as well as on translation for typologically different language pairs. The quality of the final corpus is attested by human evaluation performed on a corpus subset (100 utterances, 8 language pairs). Lastly, we showcase the usefulness of the final product on a bilingual speech retrieval task.

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A2 - Goggi, Sara

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Boito MZ, Havard W, Garnerin M, Le Ferrand E, Laurent B. MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible. In Calzolari N, Béchet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, editors, Proceedings of The 12th Language Resources and Evaluation Conference. European Language Resources Association (ELRA). 2020. p. 6486-6493